Influence of Air Temperature on the Release of Ascospores of Venturia inaequalis

Abstract

The influence of air temperature on the release pattern of Venturia inaequalis ascospores was studied by volumetric spore samplers in two spore sampling periods. In the first period (1991–1996; Passo Segni, Ferrara), 15 ascospore dispersal events were considered occurring in daylight, with high spore counts (168–5892 ascospores per m3 air per event), at an average temperature between 8.4 and 20.3°C. Both the length of the ascospore release period and distribution of airborne spores over time were significantly influenced by temperature. A logistic regression model was used to fit the proportion of ascospores trapped from the orchard air as a function of time after the beginning of the discharge event and air temperature. The accuracy of this equation was tested against data collected in the second spore sampling period (1997–2000; Sala Bolognese, Bologna, and Castelfranco, Modena); 16 dispersal events were considered, triggered by rainfall that occurred both in the dark and in daylight, with low to high spore counts (29–458 ascospores per m3 air per event), at an average temperature between 2.8 and 14.3°C. There was a general agreement between the proportion of ascospores trapped from the orchard air during these events and that estimated by using the logistic equation – in most cases, actual and estimated values showed a high coincidence. Statistical comparison showed a significant correlation (r=0.93, P < 0.01) between observed and estimated data.

Contribution of fungi to primary biogenic aerosols in the atmosphere: wet and dry discharged spores, carbohydrates, and inorganic ions

“…Blandford, UK (August) (Frankland and Gregory, 1973) ≤4.4 Didymella exitialis Edinburgh, UK (July-October) (Richardson, 1996) 0.03-5.9 Venturia inaequalis Northern Italy (March-April) (Rossi et al, 2003) (Decco et al, 1998) 0-0.25 Smuts Rochester, USA (April-September) (Decco et al, 1998) 0-0.5 various Rochester, USA (April-September) (Decco et al, 1998) 0.1-5.5 various Oklahoma, USA (May) (Troutt and Levetin, 2001) 0.6-1.6 various Oklahoma, USA (September) (Sterling et al, 1999) ≤3 various Oklahoma, USA (May-November) (Levetin, 1990) ≤30 various Harpenden, UK (July-September) Hirst, 1952) 0.3-1000 various Chichester, UK (July) (Gregory and Sreeramulu, 1958) ≤10 various Cardiff, UK (June-October) (Adams et al, 1968) 5.4 various Derby, UK (January-December) (Newson et al, 2000) ≤3 various Bern, Switzerland (June-October) (Helbling et al, 2002) 0.5-6 various Saudi Arabia (January-December) (Hasnain et al, 2005) 0-0.15 Rusts Saudi Arabia (January-December) (Hasnain et al, 2005) 0.5-4 Smuts Saudi Arabia (January-December) (Hasnain et al, 2005) ≤4.6 various Mexico City, Mexico (January-November) (Calderon et al, 1995) 1.3-2.9 various Taiwan (April-September) (Wu et al, 2004) 0.06 Rusts Taiwan (September-April) (Wu et al, 2004) 0.5 Smuts Taiwan (September-April) (Wu et al, 2004) 2.5-24 various Caxias do Sul, Brazil (January-December) (Zoppas et al, 2006) 3.6 Rusts Balbina, Brazil (July) this work 9.2 Smuts Balbina, Brazil (July) this work …”

A‐scab (Apple‐scab), a simulation model for estimating risk of Venturia inaequalis primary infections*

“…This displacement influences their probability of causing infection because ascospores released at the beginning of a discharge period may encounter different environmental conditions compared to those released at the end of the same period (MacHardy, 1996). The model uses equations [10] and [11] to distribute SRA dis over time with a time step of one hour (Rossi et al ., 2003a), so that the further steps of the infection chain will be calculated hourly.…”

Modelling the effects of temperature and wetness on the polycyclic phase of Stemphylium vesicarium, the pathogen causing purple spot on asparagus (Asparagus officinalis L.)

“…To forecast the airborne conidia, correlations between the spore catch (transformed in % of the total number of conidia) and weather parameters were made following the methods used by other authors for similar diseases (Rossi, Giosue, & Bugiani, ; Rossi, Pattori, & Bugiani, ; Rossi et al., ). For the analyses of trapped conidia, the spore data were accumulated over time and expressed relative to the maximum.…”